System and method for discrimination of central and obstructive disordered breathing events

ABSTRACT

Disordered breathing events may be classified as central, obstructive or a combination of central an obstructive in origin based on patient motion associated with respiratory effort. Central disordered breathing is associated with disrupted respiration with reduced respiratory effort. Obstructive disordered breathing is associated with disrupted respiration accompanied by respiratory effort. A disordered breathing classification system includes a disordered breathing detector and a respiratory effort motion sensor. Components of the disordered breathing classification system may be fully or partially implantable.

RELATED PATENT DOCUMENTS

This application claims the benefit of Provisional Patent ApplicationSer. No. 60/504,722, filed on Sep. 18, 2003, to which priority isclaimed pursuant to 35 U.S.C. §119(e) and which is hereby incorporatedherein by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates generally to methods and systems forclassifying disordered breathing events according to origin.

BACKGROUND OF THE INVENTION

Normal breathing occurs when the central nervous system properlyfunctions and sends signals instructing the body to breathe andobstructions to the airway are not present. Disordered breathing occurswhen a patient experiences insufficient respiration with or withoutrespiratory effort. Disordered breathing events may be classified byorigin. For example, disordered breathing can originate from adeficiency in the central nervous system (central disordered breathing)or from an obstructed airway (obstructive disordered breathing).

Central disordered breathing is caused by a disruption of the nervoussystem signals that control breathing. During central disorderedbreathing events, the patient makes no effort to breath or therespiratory effort is insufficient.

Obstructive disordered breathing generally occurs due to an obstructionof a patient's airway. For example, the patient's tongue or other softtissue of the throat may collapse into the patient's airway. Thebreathing reflex is triggered, the patient attempts to breathe, butrespiration is disrupted because of the occluded airway. Disorderedbreathing events may involve central disordered breathing, obstructivedisordered breathing, or a mixture of obstructive and central types ofdisordered breathing.

Although episodes of disordered breathing can occur when the patient isawake, they more often occur during sleep. Sleep apnea is characterizedby periods of interrupted breathing during sleep. Hypopnea is anotherform of disordered breathing characterized by periods of shallowbreathing. Sleep apnea, hypopnea and/or other forms of disorderedbreathing events may be associated with central, obstructive, or mixeddisordered breathing origins. Other forms of disordered breathing thatmay be classified according to origin may include, for example,tachypnea (rapid breathing), hyperpnea (heavy breathing), dyspnea(labored breathing), and periodic breathing (periodically waxing andwaning respiration).

A severe form of disordered breathing that generally includes periods ofcentral sleep apnea is known as Cheyne-Stokes respiration (CSR). CSR isa type of periodic breathing marked by periodic patterns of waxing andwaning respiration interrupted by periods of central apnea. CSR iscommonly associated with poor prognosis when diagnosing congestive heartfailure (CHF) patients.

Classification of disordered breathing events by origin, e.g., central,obstructive, or mixed, may be used to enhance the diagnosis ofdisordered breathing. Therapy for disordered breathing and otherconditions may be more effectively provided with knowledge of the originof breathing disorders experienced by the patient.

SUMMARY OF THE INVENTION

Embodiments of the invention are directed to methods and systems forclassifying the origin of disordered breathing events and/ordiscriminating between disordered breathing origin types. One embodimentof the invention involves a method for classifying disordered breathingin a patient. The method includes detecting a disordered breathing eventand sensing motion associated with respiratory effort during hedisordered breathing event. The disordered breathing event is classifiedbased on the sensed motion. At least one of detecting the disorderedbreathing event, sensing the motion associated with respiratory effort,and classifying the disordered breathing event are performed at least inpart implantably.

In another embodiment of the invention, a disordered breathingclassification system includes a disordered breathing detectorconfigured to detect disordered breathing in a patient. A motion sensoris configured to sense the patient's motion associated with respiratoryeffort during the disordered breathing event. A disordered breathingclassification processor is coupled to the motion sensor and thedisordered breathing detector. The disordered breathing classificationprocessor is configured to classify the disordered breathing event basedon motion associated with respiratory effort. At least one of thedisordered breathing detector, the motion sensor, and the disorderedbreathing classification processor is at least in part implantable.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a flowchart of a method of classifying a disordered breathingevent in accordance with embodiments of the invention;

FIG. 1B is a block diagram of a disordered breathing classificationsystem in accordance with embodiments of the invention;

FIG. 2 is a partial view of an implantable device that may include adisordered breathing classification system in accordance withembodiments of the invention;

FIG. 3 is a diagram illustrating an implantable transthoracic cardiacdevice that may be used in connection with discrimination of central andobstructive disordered breathing in accordance with embodiments of theinvention;

FIG. 4 is a block diagram of an implantable medical system including adisordered breathing classification system in accordance withembodiments of the invention;

FIG. 5 is a block diagram illustrating a medical system including apatient-internal device that cooperates with a patient-external deviceto implement disordered breathing classification in accordance withembodiments of the invention;

FIG. 6 is a graph of a respiration signal generated by a transthoracicimpedance sensor that may be used in connection with classification ofdisordered breathing events in accordance with embodiments of theinvention;

FIG. 7 is a graph illustrating respiration intervals used for disorderedbreathing detection according to embodiments of the invention;

FIG. 8 is a graph illustrating detection of sleep apnea and severe sleepapnea in accordance with embodiments of the invention;

FIGS. 9A and 9B illustrate respiration patterns associated with normalrespiration and abnormally shallow respiration, respectively, utilizedin accordance with embodiments of the invention;

FIG. 10 is a flow chart illustrating a method of apnea and/or hypopneadetection according to embodiments of the invention;

FIG. 11 is a respiration graph illustrating a breath interval utilizedin connection with disordered breathing detection in accordance withembodiments of the invention;

FIG. 12 is a respiration graph illustrating a hypopnea detectionapproach in accordance with embodiments of the invention;

FIGS. 13 and 14 provide charts illustrating classification of individualdisordered breathing events and series of periodically recurringdisordered breathing events, respectively, in accordance withembodiments of the invention;

FIGS. 15A-E are graphs illustrating respiration patterns that may beclassified by origin in accordance with embodiments of the invention;

FIG. 15F is a graph illustrating periodic breathing that may beclassified with respect to origin in accordance with embodiments of theinvention;

FIG. 15G is a graph illustrating Cheyne-Stokes respiration that may beclassified with respect to origin in accordance with embodiments of theinvention;

FIG. 16 is a flowchart of a method for detecting disordered breathing inaccordance with embodiments of the invention;

FIGS. 17A and 17B are graphs illustrating representative respirationsignals and accelerometer signals associated with chest wall motion forcentral and obstructive disordered breathing events, respectively, inaccordance with embodiments of the invention; and

FIGS. 18A and 18B provide a flowchart illustrating a method forclassifying a disordered breathing event and using the disorderedbreathing event classification in accordance with embodiments of theinvention.

While the invention is amenable to various modifications and alternativeforms, specifics thereof have been shown by way of example in thedrawings and will be described in detail below. It is to be understood,however, that the intention is not to limit the invention to theparticular embodiments described. On the contrary, the invention isintended to cover all modifications, equivalents, and alternativesfalling within the scope of the invention as defined by the appendedclaims.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

In the following description of the illustrated embodiments, referencesare made to the accompanying drawings that form a part hereof, and inwhich are shown by way of illustration, various embodiments by which theinvention may be practiced. It is to be understood that otherembodiments may be utilized, and structural and functional changes maybe made without departing from the scope of the present invention.

Embodiments of the invention involve classifying the origin ofdisordered breathing events. The origin of disordered breathing eventsmay be classified as central, obstructive, or a combination of centraland obstructive origin types. According to various implementations,disordered breathing events may be classified based on a patient'smotion associated with respiratory effort during the disorderedbreathing event. For example, central apnea may be identified byinsufficient respiration for at least about 10 seconds with insufficientrespiratory effort. Obstructive apnea may be identified by insufficientrespiratory inspiration for at least about 10 seconds accompanied byrespiratory effort. Respiratory effort may be detected by sensingpatient motion associated with respiratory effort during the disorderedbreathing event. The sensed motion may comprise motion of the patient'schest, abdomen, diaphragm, and/or other motion associated withrespiratory effort.

Disordered breathing episodes may be classified as central disorderedbreathing, obstructive disordered breathing, or a combination of centraland obstructive types. Various forms of disordered breathing that may beclassified with respect to origin (central, obstructive, or mixedorigin) may include, for example, apnea, hypopnea, hyperpnea, tachypnea,periodic breathing, Cheyne-Stokes respiration (CSR), and/or other formsof disordered breathing.

FIG. 1A is a flowchart of a method of classifying a disordered breathingevent in accordance with embodiments of the invention. The methodinvolves detecting 110 a disordered breathing event and sensing 120motion associated with respiratory effort during the disorderedbreathing event. Disordered breathing may be detected based on thepatient's respiration patterns, or by other methods. Motion associatedwith respiratory effort may be involve chest wall motion, abdominalmotion and/or other motions associated with respiratory effort. Thedisordered breathing event may be classified 130 as central,obstructive, or a mixture of central and obstructive types based on thepatient's movements associated with respiratory effort during thedisordered breathing event.

In one scenario, the disordered breathing event may include both centraland obstructive types. The disordered breathing event may be classifiedas a mixed central and obstructive disordered breathing event if centraldisordered breathing is classified during one portion of the disorderedbreathing event and obstructive disordered breathing is classifiedduring another portion of the disordered breathing event.

FIG. 1B is a block diagram of a disordered breathing classificationsystem 100 in accordance with embodiments of the invention. Thedisordered breathing classification system 100 illustrated in FIG. 1Bincludes a disordered breathing classification processor 150 thatreceives signals from a disordered breathing detector 140 and a motionsensor 160.

The disordered breathing detector 140 includes at least one sensor 135for detecting a physiological signal indicative of disordered breathing.The sensor signals are communicated to the disordered breathingprocessor 137. The disordered breathing processor 137 analyzes thesensor signals and may determine that a disordered breathing event is inprogress based on the analysis.

In one implementation, the sensor 135 generates a signal modulated bypatient respiration. Such a signal may be generated, for example, by atransthoracic impedance sensor, an airflow meter, or by other sensingmethods. A disordered breathing event may be detected based on thepatient's breath intervals and/or tidal volume as described more fullybelow.

The motion sensor 160 may be configured to sense chest wall motion,abdominal motion, and/or other patient movement indicative ofrespiratory effort. The motion sensor 160 generates a signal indicativeof respiratory effort that is communicated to the disordered breathingclassification processor 150.

The sensors 135, 160 may comprise any number of patient-internal and/orpatient-external sensors coupled through leads or wirelessly to othercomponents of the disordered breathing classification system 100. Invarious embodiments, a signal indicative of the patient's respirationmay be acquired using an implantable or patient-external transthoracicimpedance sensor, blood oxygen sensor, microphone, flow meter, or byother patient-internal and/or patient-external sensing methods.

Sensing chest, abdominal, or other respiratory effort motion may beaccomplished using a patient-internal or patient-external sensingdevice. In one example, patient motion associated with respiratoryeffort may be sensed using an implanted or patient-externalaccelerometer. The accelerometer may be incorporated as a component ofan implanted medical device.

In another example, motion associated with respiratory effort may bedetected based on changes in an electromyogram (EMG) sensor signal. AnEMG sensor may be positioned internally or externally to detectelectrical activity of a patient's intercostal, pectoral and/ordiaphragmatic muscles indicative of motion, for example. In yet anotherexample, motion associated with respiratory effort may be detected usinga transthoracic impedance sensor. The patient's transthoracic impedanceis modulated as the chest wall and/or abdomen moves during inspiratoryattempts. Transthoracic impedance may be sensed using intracardiacelectrodes, subcutaneous electrodes, or patient-external electrodespositioned at appropriate locations in, on, or about the patient'sthorax for example.

A disordered breathing event may be classified as a central, obstructiveor mixed type based on the based on the patient's respiratory effortsduring disordered breathing episodes. The disordered breathingclassification processor 150 may discriminate between central andobstructive disordered breathing events using signals received from themotion sensor 160 and the disordered breathing detector 140. If patientmotion associated with respiratory effort is of sufficient magnitudeduring disordered breathing, then the disordered breathingclassification processor 150 may determine that the disordered breathingevent is obstructive in origin. If respiratory effort motion isinsufficient during the disordered breathing event, then the disorderedbreathing classification processor 150 may be classify the disorderedbreathing event as central in origin. If the respiratory effort motionis sufficient during one portion of the disordered breathing episode,but is insufficient during another portion, then the disorderedbreathing classification processor 150 may classify the episode as amixture of central and obstructive types.

In one configuration, the disordered breathing classification system 100may be fully patient-external. In another configuration, some functionsof the disordered breathing classification system may be implemented inan implantable device and other functions may be implemented as apatient external device. The implantable and the patient-externaldisordered breathing classification system components may be coupledthrough leads or a wireless communications link, such as through a BlueTooth or a proprietary wireless communication link.

In yet another configuration, the disordered breathing classificationsystem may be fully implantable. A fully implantable disorderedbreathing classification system may be incorporated, for example, as acomponent of a cardiac device such as a pacemaker, defibrillator,cardiac resynchronizer, implantable cardiac monitor, or otherimplantable medical device.

FIG. 2 is a partial view of an implantable device that may include adisordered breathing classification system in accordance withembodiments of the invention. The implantable device illustrated in FIG.2 represents a cardiac rhythm management device (CRM) 200 that includesan implantable pulse generator 205 electrically and physically coupledto an intracardiac lead system 210. Portions of the intracardiac leadsystem 210 are inserted into the patient's heart 290. The intracardiaclead system 210 includes one or more electrodes configured to senseelectrical cardiac activity of the heart, provide electrical stimulationto the heart, and/or to sense the patient's transthoracic impedance.Portions of the housing 201 of the pulse generator 205 may optionallyserve as a can electrode.

Communications circuitry is disposed within the housing 201 forfacilitating communication between the pulse generator 205 and anexternal communication device, such as a portable or bed-sidecommunication station, patient-carried/worn communication station, orexternal programmer, for example. The communications circuitry can alsofacilitate unidirectional or bidirectional communication with one ormore external, cutaneous, or subcutaneous physiologic or non-physiologicsensors, patient-input devices and/or information systems.

The pulse generator 205 may incorporate a motion detector 220 that maybe used to sense the patient's chest wall movements associated withrespiratory effort. The motion detector 220 may be implemented as anaccelerometer positioned, for example, in or on the housing 201 of thepulse generator 205.

The lead system 210 of the CRM 200 may incorporate a transthoracicimpedance sensor used to sense the patient's respiration. In oneconfiguration, the transthoracic impedance sensor may include one ormore intracardiac impedance electrodes. 231-233 positioned in one ormore chambers of the heart 290 and impedance drive/sense circuitry 230within the housing of the pulse generator 205.

The impedance drive/sense circuitry 230 generates a current that flowsthrough the tissue between an impedance drive electrode 233 and a canelectrode on the housing 201 of the pulse generator 205. The voltage atthe impedance sense electrode 231, 232 relative to the can electrodechanges as the patient's transthoracic impedance changes. The voltagesignal developed between the impedance sense electrode 231, 232 and thecan electrode is detected by the impedance drive/sense circuitry 230.

The voltage signal developed at the impedance sense electrode, 231, 232,illustrated in FIG. 6, is proportional to the patient's transthoracicimpedance. Transthoracic impedance increases during respiratoryinspiration and decreases during respiratory expiration. Thepeak-to-peak transition of the impedance, illustrated in FIG. 6, isproportional to the amount of air inhaled in one breath, denoted thetidal volume. The amount of air moved per minute is denoted the minuteventilation.

One or more pace/sense electrodes 251-255 may be positioned in one ormore heart chambers for sensing electrical signals from the patient'sheart 290 and/or delivering pacing pulses to the heart 290. Thesense/pace electrodes 251-255 can be used to sense and pace one or morechambers of the heart, including the left ventricle, the rightventricle, the left atrium, and/or the right atrium. The lead system 210may optionally include one or more defibrillation electrodes 241, 242for delivering defibrillation/cardioversion shocks to the heart.

The pulse generator 205 may incorporate circuitry for detecting cardiacarrhythmias and circuitry for providing therapy in the form ofelectrical stimulation delivered to the heart through the lead system210. A disordered breathing classification processor may also beincorporated within the pulse generator housing for classifyingdisordered breathing events in accordance with embodiments of theinvention.

FIG. 3 is a diagram illustrating another configuration of an implantablemedical device that may be used in connection with classification ofdisordered breathing in accordance with embodiments of the invention.The implantable device illustrated in FIG. 3 is an implantabletransthoracic cardiac sensing and/or stimulation (ITCS) device that maybe implanted under the skin in the chest region of a patient. The ITCSdevice may, for example, be implanted subcutaneously such that all orselected elements of the device are positioned on the patient's front,back, side, or other body locations suitable for sensing cardiacactivity and delivering cardiac stimulation therapy. Elements of theITCS device may be located at several different body locations, such asin the chest, abdominal, or subclavian region with electrode elementsrespectively positioned at different regions near, around, in, or on theheart.

The ITCS device may incorporate a disordered breathing system fordiscriminating between types of disordered breathing. Portions of theclassification system may be positioned within the primary housing 302of the ITCS device. The primary housing (e.g., the active or non-activecan) of the ITCS device, for example, may be configured for positioningoutside of the rib cage at an intercostal or subcostal location, withinthe abdomen, or in the upper chest region (e.g., subclavian location,such as above the third rib). In one implementation, one or moreelectrodes may be located on the primary housing and/or at otherlocations about, but not in direct contact with the heart, great vesselor coronary vasculature.

In another implementation, one or more electrodes may be located indirect contact with the heart, great vessel or coronary vasculature,such as via one or more leads implanted by use of conventionaltransvenous delivery approaches. In another implementation, for example,one or more subcutaneous electrode subsystems or electrode arrays may beused to sense cardiac activity and deliver cardiac stimulation energy inan ITCS device configuration employing an active can or a configurationemploying a non-active can. Electrodes may be situated at anteriorand/or posterior locations relative to the heart.

Communications circuitry is disposed within the housing 302 forfacilitating communication between the ITCS device and an externalcommunication device, such as a portable or bed-side communicationstation, patient-carried/worn communication station, or externalprogrammer, for example. The communications circuitry can alsofacilitate unidirectional or bidirectional communication with one ormore external, cutaneous, or subcutaneous: physiologic ornon-physiologic sensors. The housing 302 is typically configured toinclude one or more electrodes (e.g., can electrode and/or indifferentelectrode).

In the configuration shown in FIG. 3, a subcutaneous electrode assembly307 can be positioned under the skin in the chest region and situateddistal from the housing 302. The subcutaneous and, if applicable,housing electrode(s) can be positioned about the heart at variouslocations and orientations, such as at various anterior and/or posteriorlocations relative to the heart. The subcutaneous electrode assembly 307is coupled to circuitry within the housing 302 via a lead assembly 306.One or more conductors (e.g., coils or cables) are provided within thelead assembly 306 and electrically couple the subcutaneous electrodeassembly 307 with circuitry in the housing 302. One or more chest wallmotion sensors and/or transthoracic impedance electrodes along with oneor more cardiac sense, sense/pace or defibrillation electrodes can besituated on the elongated structure of the lead assembly 306, thehousing 302, and/or the distal electrode assembly (shown as subcutaneouselectrode assembly 307 in the configuration shown in FIG. 3).

In particular configurations, the ITCS device may perform functionstraditionally performed by cardiac rhythm management devices, such asproviding various cardiac monitoring, pacing and/orcardioversion/defibrillation functions. Exemplary pacemaker circuitry,structures and functionality, aspects of which can be incorporated in anITCS device of a type that may benefit from multi-parameter sensingconfigurations, are disclosed in commonly owned U.S. Pat. Nos.4,562,841; 5,284,136; 5,376,476; 5,036,849; 5,540,727; 5,836,987;6,044,298; and 6,055,454, which are hereby incorporated herein byreference in their respective entireties. It is understood that ITCSdevice configurations can provide for non-physiologic pacing support inaddition to, or to the exclusion of, bradycardia and/or anti-tachycardiapacing therapies. Exemplary cardiac monitoring circuitry, structures andfunctionality, aspects of which can be incorporated in an ITCS of thepresent invention, are disclosed in commonly owned U.S. Pat. Nos.5,313,953; 5,388,578; and 5,411,031, which are hereby incorporatedherein by reference in their respective entireties.

An ITCS device can incorporate circuitry, structures and functionalityof the subcutaneous implantable medical devices disclosed in commonlyowned U.S. Pat. Nos. 5,203,348; 5,230,337; 5,360,442; 5,366,496;5,397,342; 5,391,200; 5,545,202; 5,603,732; and 5,916,243 and commonlyowned U.S. patent applications “Subcutaneous Cardiac Sensing,Stimulation, Lead Delivery, and Electrode Fixation Systems and Methods,”Ser. No. 60/462,272, filed Apr. 11, 2003, and HybridTransthoracic/Intrathoracic Cardiac Stimulation Devices and Methods,”Ser. No. 10/462,001, filed Jun. 13, 2003, and “Methods and SystemsInvolving Subcutaneous Electrode Positioning Relative to A Heart,” Ser.No. 10/465,520, filed Jun. 19, 2003 which are incorporated by reference.

In FIG. 3, there is shown a configuration of a transthoracic cardiacsensing and/or stimulation (ITCS) device incorporating a disorderedbreathing classification system having components implanted in the chestregion of a patient at different locations. The disordered breathingclassification system may be used to discriminate between central andobstructive disordered breathing events and/or to classify disorderedbreathing events in accordance with embodiments of the invention. In theparticular configuration shown in FIG. 3, the ITCS device includes aprimary housing 302, lead assembly 306, and a subcutaneous electrodeassembly 307. Various sensing, detection, processing, and energydelivery circuitry for disordered breathing classification and/ordiscrimination can be positioned within, on, and/or about the componentsof the ITCS. For example, a disordered breathing classificationprocessor 304, a patient motion sensor 305, and/or portions of adisordered breathing detector may be positioned on or within the primaryhousing 302, the lead assembly 306, and/or the subcutaneous electrodeassembly 307 of the ITCS device.

In one embodiment, a disordered breathing classification processor 304is located within the primary housing 302 of the ITCS. The patientmotion sensor 305 comprises an accelerometer positioned in or on theprimary housing 302 of the ITCS. The accelerometer is configured tosense patient motion associated with respiratory effort. In thisembodiment, a transthoracic impedance sensor is used to sense patientrespiration. The transthoracic impedance sensor may include impedancedrive/sense circuitry within the housing 302 coupled to a can electrodeand to one or more impedance electrodes 308, 309 positioned on thesubcutaneous electrode assembly 307. The impedance drive circuitrygenerates a current that flows between a subcutaneous impedance driveelectrode 309 and the can electrode on the primary housing 302 of theITCS device. The voltage at a subcutaneous impedance sense electrode 308relative to the can electrode changes as the patient's transthoracicimpedance changes. The voltage signal developed between the impedancesense electrode 308 and the can electrode is sensed by the impedancesense circuitry, producing a signal such as that depicted in FIG. 6.

As previously discussed, the transthoracic impedance signal is relatedto patient respiration, with impedance increasing during respiratoryinspiration and decreasing with respiratory expiration. Respirationsignals generated by the transthoracic impedance sensor may be used toby the disordered breathing detector to detect disordered breathing.Respiration signals may be used in conjunction with patient motionsignals associated with respiratory effort for classification and/ordiscrimination of the origin of disordered breathing events.

FIG. 4 is a block diagram of an implantable medical system 400comprising an implantable cardiac device 410 incorporating a disorderedbreathing classification system in accordance with embodiments of theinvention. The cardiac device 410 includes a cardiac therapy circuit 415and a cardiac sense circuit 420 coupled through a lead system to cardiacelectrodes 425. The cardiac electrodes 425 are electrically coupled tothe patient's heart for sensing electrical cardiac signals and/ordelivering therapy to the heart in the form of electrical stimulationenergy, e.g., pacing pulses and/or defibrillation/cardioversion shocks.

The cardiac device 410 illustrated in FIG. 4 includes a disorderedbreathing classification processor 430 coupled to an accelerometer 440and to a disordered breathing detector 436. The accelerometer 440 sensespatient motion associated with respiratory effort, e.g., motion of thechest wall, abdomen diaphragm, and/or thorax and generates a signalcorresponding to patient movement associated with respiratory effort.Transthoracic impedance drive/sense circuitry 435 and transthoracicimpedance electrodes 445 together form a transthoracic impedance sensorcapable of producing a signal representative of the patient'srespiration. The disordered breathing detector 436 may detect disorderedbreathing episodes based on the patient's respiration patterns, or byother methods. The disordered breathing classification processor 430classifies the disordered breathing events as central, obstructive ormixed disordered breathing events based on signals received from theaccelerometer 440 and the disordered breathing detector 436.

Various conditions affecting the patient that may be used for disorderedbreathing detection can be acquired using patient-internal orpatient-external sensors 471, patient input devices 472 and/or otherinformation systems 473. The one or more of the conditions sensed usingthe sensors 471, patient input device 472, and/or other informationsystems 473 may be used in addition to the transthoracic impedancesignal or in place of the transthoracic impedance signal for disorderedbreathing detection as described more fully below.

The sensors 471 may comprise patient-internal and/or patient-externalsensors coupled through leads or wirelessly to the implantable device410. The patient input device 472 allows the patient to inputinformation relevant to disordered breathing detection. For example, thepatient input device 472 may be particularly useful for inputtinginformation concerning patient-known information relevant to disorderedbreathing detection, such as information related to patient sleep times,smoking, drug use, and/or patient perceptions that are not automaticallysensed or detected by the medical device 410.

The medical device 410 may also be coupled to one or more informationsystems 473, such as network-connected servers. The implantable device410, may access the information systems 473 to acquire information aboutconditions associated with an increased or decreased incidence ofdisordered breathing in the patient. For example, the implantable device410 may access an air quality website to acquire information about theambient pollution index that may be used in disordered breathingdetection.

The medical device 410 includes a memory circuit 460 that may be used tostore data and/or programming commands. For example, the memory circuit460 may be used to store information related to disordered breathing,such as information about the occurrence of one or more disorderedbreathing events, the classified origin of one or more disorderedbreathing events, and/or conditions or thresholds used for disorderedbreathing detection. Stored information maybe wirelessly transmitted toa remote device 455, such as a device programmer and/or a patientmanagement server. The communications circuitry 450 of the implantabledevice 410 may be used to implement wireless communication with theremote device 455 through a wireless communication link, e.g., Bluetoothor proprietary wireless link. Further, the communications circuitry 450may be used to couple the medical device 410 to one or more internal,external, cutaneous, subcutaneous physiologic or non-physiologicsensors, patient input devices and/or information systems.

Embodiments described herein may be used within the context of anadvanced patient management system. Advanced patient management systemsinvolve a system of medical devices that are accessible through variouscommunications technologies. For example, patient data may be downloadedfrom one or more of the medical devices periodically or on command, andstored at a patient information server. The physician and/or the patientmay communicate with the medical devices and the patient informationserver, for example, to submit or acquire patient data or to initiate,terminate or modify therapy.

Methods, structures, or techniques described herein relating to advancedpatient management, such as remote patient monitoring, diagnosis, and/ortherapy, or other advanced patient management methodologies canincorporate features of one or more of the following references: U.S.Pat. Nos. 6,221,011, 6,270,457, 6,280,380, 6,312,378, 6,336,903,6,358,203, 6,368,284, 6,398,728, and 6,440,066 which are incorporated byreference.

Disordered breathing may be more effectively classified using acoordinated approach. Various embodiments of the invention areimplemented using medical systems employing one or a number ofpatient-external and/or patient-internal medical devices. The medicaldevices may communicate or otherwise operate in concert to provide morecomprehensive patient monitoring, diagnosis, and/or therapy fordisordered breathing or other medical dysfunctions.

The block diagram of FIG. 5 illustrates a medical system 500 including apatient-internal device 510 that cooperates with a patient-externaldevice 520 to implement disordered breathing classification inaccordance with embodiments of the invention. The patient-internaldevice 510 may comprise, for example, an implantable cardiac rhythmmanagement system (CRM) such as a pacemaker, defibrillator, cardiacresynchronizer, or the like.

The patient-external device 520 may comprise, for example, an externalbreathing therapy device such as a continuous positive airway pressuredevice (CPAP), bi-level positive airway pressure device (bi-PAP) orother positive airway pressure device, generically referred to herein asxPAP devices. An xPAP device 520 develops a positive air pressure thatis delivered to the patient's airway through tubing 552 and mask 554connected to the xPAP device 520. Positive airway pressure devices areoften used to treat disordered breathing. In one configuration, forexample, the positive airway pressure provided by the xPAP device 520acts as a pneumatic splint keeping the patient's airway open andreducing the severity and/or number of occurrences of disorderedbreathing events due to airway obstruction. In addition to deliveringbreathing therapy, sensors associated with the xPAP device 520, locatedon the xPAP mask or elsewhere, may provide information useful to anumber of monitoring and/or diagnostic functions. For example, the xPAPdevice 520 may sense respiration using an oxygen sensor, a microphone, aflow meter, and/or other respiration sensing methods.

A disordered breathing detector and/or a disordered breathingclassification processor may be incorporated in either thepatient-internal CRM 510 device, the patient-external xPAP 520 device,or a remote computing device such as a patient management server 530.The CRM 510 may provide a first set of monitoring, diagnostic, and/ortherapeutic functions to the patient. The xPAP device 520 may provide asecond set of monitoring, diagnostic, and/or therapeutic functions tothe patient. The CRM device 510, the xPAP device 520, or both mayinclude sensors for sensing patient movement and/or respiration used fordisordered breathing classification.

In one embodiment, the CRM device 510 may sense both respiration andpatient movement associated with respiratory-effort. The sensedinformation may be transmitted to the xPAP device 520. Classification ofdisordered breathing events as to central, obstructive, or mixed originmay be implemented in the xPAP device based on the patient movement andrespiration information transmitted from the CRM device 510.

In another embodiment, the CRM device 510 may sense patient movementassociated with respiratory effort and the CPAP device 510 may sensepatient respiration. Patient respiration information may be transmittedfrom the CPAP 520 device to the CRM device 510. The respirationinformation may be used by the CRM device 510 along with the patientmovement information for classifying the disordered breathing events.

In yet another embodiment, CRM device 510 may sense patient movement andthe CPAP device 510 may sense patient respiration. Patient respirationinformation may be transmitted from the CPAP 520 device and the CRMdevice 510 to a remote patient management server 530. The respirationand patient movement information may be used by the patient managementserver 530 for classifying disordered breathing events.

The processes described herein involve detecting a disordered breathingevent and evaluating movements indicative of respiratory effort thatoccur during the disordered breathing event. A disordered breathingevent may be detected by sensing and analyzing various conditionsaffecting the patient and associated with disordered breathing. Table 1provides a representative set of patient conditions that may be used inconnection with disordered breathing detection in accordance withembodiments of the invention. Table 1 also provides illustrative sensingmethods that may be employed to sense the conditions.

Conditions used for disordered breathing detection may include bothphysiological and non-physiological contextual conditions affecting thepatient. Physiological conditions may include a broad category ofconditions associated with the internal functioning of the patient'sphysiological systems, including the cardiovascular, respiratory,nervous, muscle, and other body systems. Examples of physiologicalconditions that may be useful in the detection of disordered breathinginclude blood chemistry, patient posture, patient activity, respirationpatterns, among others.

Contextual conditions are non-physiological conditions representingpatient-external or background conditions. Contextual conditions may bebroadly defined to include present environmental conditions, such aspatient location, ambient temperature, humidity, air pollution index.Contextual conditions may also include historical/background conditionsrelating to the patient, including the patient's normal sleep time andthe patient's medical history, for example. Methods and systems fordetecting some contextual conditions, including, for example, proximityto bed detection, are described in commonly owned U.S. PatentApplication entitled “Methods and Devices for Detection of Context WhenAddressing A Medical Condition of a Patient,” Ser. No. 10/269611, filedOct. 11, 2002, which is incorporated by reference herein in itsentirety. TABLE 1 Sensor type or Detection Condition Type Conditionmethod Physiological Cardiovascular Heart rate EGM, ECG System Heartrate variability QT interval Ventricular filling pressure Intracardiacpressure sensor Blood pressure Blood pressure sensor Respiratory SystemSnoring Accelerometer Microphone Respiration pattern Transthoracicimpedance (Tidal volume Minute sensor (AC) ventilation Respiratory rate)Patency of upper airway Intrathoracic impedance sensor Pulmonarycongestion Transthoracic impedance sensor (DC) Nervous SystemSympathetic nerve activity Muscle sympathetic nerve Activity sensorBrain activity EEG Blood Chemistry CO2 saturation Blood analysis O2saturation Blood alcohol content Adrenalin Brain Natriuretic Peptide(BNP) C-Reactive Protein Drug/Medication/Tobacco use Muscle SystemMuscle atonia EMG Eye movement EOG Patient activity Accelerometer, MV,etc. Limb movements Accelerometer, EMG Jaw movements Accelerometer, EMGPosture Multi-axis accelerometer Contextual Environmental Ambienttemperature Thermometer Humidity Hygrometer Pollution Air qualitywebsite Time Clock Barometric pressure Barometer Ambient noiseMicrophone Ambient light Photodetector Altitude Altimeter Location GPS,proximity sensor Proximity to bed Proximity to bed sensorHistorical/Background Historical sleep time Patient input, previouslydetected sleep onset times Medical history Patient input Age Recentexercise Weight Gender Body mass index Neck size Emotional statePsychological history Daytime sleepiness Patient perception of sleepquality Drug, alcohol, nicotine use

Table 2 provides examples of how a representative subset of thephysiological and contextual conditions listed in Table 1 may be used inconnection with disordered breathing detection.

It will be appreciated that patient conditions and detection methodsother than those listed in Tables 1 and 2 may be used for disorderedbreathing detection and are considered to be within the scope of theinvention. TABLE 2 Examples of how condition may be used in disorderedCondition Type Condition breathing detection Physiological Heart rateDecrease in heart rate may indicate disordered breathing episode.Increase in heart rate may indicate autonomic arousal from a disorderedbreathing episode. Decrease in heart rate may indicate the patient isasleep. Heart rate variability Disordered breathing causes heart ratevariability to decrease. Changes in HRV associated with sleep disorderedbreathing may be observed while the patient is awake or asleepVentricular filling May be used to identify/predict pulmonary congestionpressure associated with respiratory disturbance. Blood pressure Swingsin on-line blood pressure measures are associated with apnea. Disorderedbreathing generally increases blood pressure variability - these changesmay be observed while the patient is awake or asleep. Snoring Snoring isassociated with a higher incidence of obstructive sleep apnea and may beused to detect disordered breathing. Respiration Respiration patternsincluding, e.g., respiration rate, pattern/rate may be used to detectdisordered breathing episodes. Respiration patterns may be used todetermine the type of disordered breathing. Respiration patterns may beused to detect that the patient is asleep. Patency of upper Patency ofupper airway is related to obstructive sleep airway apnea and may beused to detect episodes of obstructive sleep apnea. Pulmonary Pulmonarycongestion is associated with respiratory congestion disturbances.Sympathetic nerve End of apnea associated with a spike in SNA. Changesactivity in SNA observed while the patient is awake or asleep may beassociated with sleep disordered breathing CO2 Low CO2 levels initiatecentral apnea. O2 O2 desaturation occurs during severe apnea/hypopneaepisodes. Blood alcohol content Alcohol tends to increase incidence ofsnoring & obstructive apnea. Adrenalin End of apnea associated with aspike in blood adrenaline. BNP A marker of heart failure status, whichis associated with Cheyne-Stokes Respiration C-Reactive Protein Ameasure of inflammation that may be related to apnea.Drug/Medication/Tobacco These substances may affect the incidence ofboth use central & obstructive apnea. Muscle atonia Muscle atonia may beused to detect REM and non- REM sleep. Eye movement Eye movement may beused to detect REM and non- REM sleep. Contextual Temperature Ambienttemperature may be a condition predisposing the patient to episodes ofdisordered breathing and may be useful in disordered breathingdetection. Humidity Humidity may be a condition predisposing the patientto episodes of disordered breathing and may be useful in disorderedbreathing detection. Pollution Pollution may be a condition predisposingthe patient to episodes of disordered breathing and may be useful indisordered breathing detection. Posture Posture may be used to confirmor determine the patient is asleep. Activity Patient activity may beused in relation to sleep detection. Location Patient location may usedto determine if the patient is in bed as a part of sleep detection.Altitude Lower oxygen concentrations at higher altitudes tends to causemore central apnea

Detection of disordered breathing may involve comparing one condition ormultiple conditions to one or more thresholds or other indicesindicative of disordered breathing. A threshold or other indexindicative of disordered breathing may comprise a predetermined level ofa particular condition, e.g., blood oxygen level less than apredetermined amount. A threshold or other index indicative ofdisordered breathing may comprises a change in a level of a particularcondition, e.g., heart rate decreasing from a sleep rate to lower ratewithin a predetermined time interval.

In one approach, the relationships between the conditions may beindicative of disordered breathing. In this approach, disorderedbreathing detection may be based on the existence and relative valuesassociated with two or more conditions. For example, if condition A ispresent at a level of x, then condition B must also be present at alevel of f(x) before a disordered breathing detection is made.

The thresholds and/or relationships indicative of disordered breathingmay be highly patient specific. The thresholds and/or relationshipsindicative of disordered breathing may be determined on a case-by-casebasis by monitoring the conditions and monitoring disordered breathingepisodes. The analysis may involve determining levels of the monitoredconditions and/or relationships between the monitored conditionsassociated, e.g., statistically correlated, with disordered breathingepisodes. The thresholds and/or relationships used in disorderedbreathing detection may be updated periodically to track changes in thepatient's response to disordered breathing.

In various implementations, episodes of disordered breathing may bedetected through analysis of the patient's respiration patterns. Methodsand systems of disordered breathing detection based on respirationpatterns are further described in commonly owned U.S. patent applicationentitled “Detection of Disordered Breathing,” Ser. No. 10/309,770,attorney docket number GUID.054PA, filed Dec. 4, 2002 which isincorporated by reference.

FIG. 6 illustrates normal respiration signal generated by atransthoracic impedance sensor. Transthoracic impedance increases duringrespiratory inspiration and decreases during respiratory expiration. Anormal “at rest” respiration pattern, e.g., during non-REM sleep,includes regular, rhythmic inspiration-expiration cycles withoutsubstantial interruptions.

In various embodiments, episodes of disordered breathing may be detectedby monitoring the respiratory waveform signal generated by atransthoracic impedance sensor. In one example, when the tidal volume(TV) of the patient's respiration, as indicated by the transthoracicimpedance signal, falls below a hypopnea threshold, then a hypopneaevent is declared. A hypopnea event may be declared, for example, if thepatient's tidal volume falls below about 50% of a recent average tidalvolume or other baseline tidal volume value. If the patient's tidalvolume falls further to an apnea threshold, e.g., about 10% of therecent average tidal volume or other baseline value, an apnea event isdeclared.

In another embodiment, detection of disordered breathing involvesdefining and analyzing respiratory cycle intervals. FIG. 7 is a graphillustrating respiration intervals used for disordered breathingdetection according to embodiments of the invention. A respiration cycleis divided into an inspiration period 730 corresponding to the patientinhaling, an expiration period 750, corresponding to the patientexhaling, and a non-breathing period 760 occurring between inspiration730 and expiration 750. Respiration intervals are established usinginspiration 710 and expiration 720 thresholds. The inspiration threshold710 marks the beginning of an inspiration period 730 and is determinedby the transthoracic impedance signal rising above the inspirationthreshold 710. The inspiration period 730 ends when the transthoracicimpedance signal is maximum 740. A maximum transthoracic impedancesignal 740 corresponds to both the end of the inspiration interval 730and the beginning of the expiration interval 750. The expirationinterval 750 continues until the transthoracic impedance falls below anexpiration threshold 720. A non-breathing interval 760 starts from theend of the expiration period 750 and continues until the beginning ofthe next inspiration period 770.

Detection of sleep apnea and/or severe sleep apnea according toembodiments of the invention is illustrated in FIG. 8. The patient'srespiration signals are monitored and the respiration cycles are definedaccording to inspiration 830, expiration 850, and non-breathing 860intervals as described in connection with FIG. 7. A condition of sleepapnea is detected when a non-breathing period 860 exceeds a firstpredetermined interval 890, denoted the sleep apnea interval. Acondition of severe sleep apnea is detected when the non-breathingperiod 860 exceeds a second predetermined interval 895, denoted thesevere sleep apnea interval. For example, sleep apnea may be detectedwhen the non-breathing interval exceeds about 10 seconds, and severesleep apnea may be detected when the non-breathing interval exceedsabout 20 seconds.

Hypopnea is a condition of disordered breathing characterized byabnormally shallow breathing. FIGS. 9A-9B are graphs of tidal volumederived from transthoracic impedance measurements. The graphs comparethe tidal volume of a normal breathing cycle to the tidal volume of ahypopnea episode. FIG. 9A illustrates normal respiration tidal volumeand rate. As shown in FIG. 9B, hypopnea involves a period of abnormallyshallow respiration.

According to an embodiment of the invention, hypopnea may be detected bycomparing a patient's respiratory tidal volume to a hypopnea tidalvolume threshold. The tidal volume for each respiration cycle is derivedfrom transthoracic impedance measurements acquired in the mannerdescribed above. The hypopnea tidal volume threshold may be establishedusing clinical results providing a representative tidal volume andduration of hypopnea events. In one configuration, hypopnea is detectedwhen an average of the patient's respiratory tidal volume taken over aselected time interval falls below the hypopnea tidal volume threshold.Furthermore, various combinations of hypopnea cycles, breath intervals,and non-breathing intervals may be used to detect hypopnea, where thenon-breathing intervals are determined as described above.

FIG. 10 is a flow chart illustrating a method of apnea and/or hypopneadetection according to embodiments of the invention. Various parametersare established 1001 before analyzing the patient's respiration fordisordered breathing episodes, including, for example, inspiration andexpiration thresholds, sleep apnea interval, severe sleep apneainterval, and hypopnea tidal volume threshold.

The patient's transthoracic impedance is determined 1005 as described inmore detail above. If the transthoracic impedance exceeds 1010 theinspiration threshold, the beginning of an inspiration interval isdetected 1015. If the transthoracic impedance remains below 1010 theinspiration threshold, then the impedance signal is checked 1005periodically until inspiration 1015 occurs.

During the inspiration interval, the patient's transthoracic impedanceis monitored until a maximum value of the transthoracic impedance isdetected 1020. Detection of the maximum value signals an end of theinspiration period and a beginning of an expiration period 1035.

The expiration interval is characterized by decreasing transthoracicimpedance. When the transthoracic impedance falls 1040 below theexpiration threshold, a non-breathing interval is detected 1055.

If the transthoracic impedance does not exceed 1060 the inspirationthreshold within a first predetermined interval 1065, denoted the sleepapnea interval, then a condition of sleep apnea is detected 1070. Severesleep apnea is detected 1080 if the non-breathing period extends beyonda second predetermined interval 1075, denoted the severe sleep apneainterval.

When the transthoracic impedance exceeds 1060 the inspiration threshold,the tidal volume from the peak-to-peak transthoracic impedance iscalculated, along with a moving average of past tidal volumes 1085. Thepeak-to-peak transthoracic impedance provides a value proportional tothe tidal volume of the respiration cycle. This value is compared to ahypopnea tidal volume threshold 1090. If the peak-to-peak transthoracicimpedance is consistent with the hypopnea tidal volume threshold 1090for a predetermined time 1092, then a hypopnea cycle is detected 1095.

Additional sensors, such as motion sensors and/or posture sensors, maybe used to confirm or verify the detection of a sleep apnea or hypopneaepisode. The additional sensors may be employed to prevent false ormissed detections of sleep apnea/hypopnea due to posture and/or motionrelated artifacts.

Another embodiment of the invention involves classifying respirationpatterns as disordered breathing episodes based on the breath intervalsand/or tidal volumes of one or more respiration cycles within therespiration patterns. According to this embodiment, the duration andtidal volumes associated with a respiration pattern are compared toduration and tidal volume thresholds. The respiration pattern isdetected as a disordered breathing episode based on the comparison.

According to principles of the invention, a breath interval isestablished for each respiration cycle. A breath interval represents theinterval of time between successive breaths, as illustrated in FIG. 11.A breath interval 1130 may be defined in a variety of ways, for example,as the interval of time between successive maxima 1110, 1120 of theimpedance signal waveform.

Detection of disordered breathing, in accordance with embodiments of theinvention, involves the establishment of a duration threshold and atidal volume threshold. If a breath interval exceeds the durationthreshold, an apnea event is detected. Detection of sleep apnea, inaccordance with this embodiment, is illustrated in the graph of FIG. 11.Apnea represents a period of non-breathing. A breath interval 1130exceeding a duration threshold 1140 comprises an apnea episode.

Hypopnea may be detected using the duration threshold and tidal volumethreshold. A hypopnea event represents a period of shallow breathing.Each respiration cycle in a hypopnea event is characterized by a tidalvolume less than the tidal volume threshold. Further, the hypopnea eventinvolves a period of shallow breathing greater than the durationthreshold.

A hypopnea detection approach, in accordance with embodiments of theinvention, is illustrated in FIG. 12. Shallow breathing is detected whenthe tidal volume of one or more breaths is below a tidal volumethreshold 1210. If the shallow breathing continues for an intervalgreater than a duration threshold 1220, then the breathing patternrepresented by the sequence of shallow respiration cycles is classifiedas a hypopnea event.

FIGS. 13 and 14 provide charts illustrating classification of individualdisordered breathing events and series of periodically recurringdisordered breathing events, respectively. As illustrated in FIG. 13,individual disordered breathing events may be grouped into apnea,hypopnea, tachypnea and other disordered breathing events. Apnea eventsare characterized by a reduction of breathing. Intervals of reducedrespiration are classified as hypopnea events. Tachypnea events includeintervals of rapid respiration characterized by an elevated respirationrate.

As illustrated in FIG. 13, apnea and hypopnea events may be furthersubdivided as either central events, related to central nervous systemdysfunction, or obstructive events, caused by upper airway obstruction.A tachypnea event may be further classified as a hyperpnea event,represented by hyperventilation, i.e., rapid deep breathing. A tachypneaevent may alternatively be classified as rapid breathing, typically ofprolonged duration.

FIG. 14 illustrates classification of combinations of periodicallyrecurring disordered breathing events. Periodic breathing may beclassified as obstructive, central or mixed. Obstructive periodicbreathing is characterized by cyclic respiratory patterns with anobstructive apnea or hypopnea event in each cycle. Central periodicbreathing involves cyclic respiratory patterns including a central apneaor hypopnea event in each cycle. Periodic breathing, illustrated in FIG.15F, may also be of mixed origin. Mixed origin periodic breathing ischaracterized by cyclic respiratory patterns having a mixture ofobstructive and central apnea events in each cycle. Cheyne-Stokesrespiration, illustrated in FIG. 15G, is a particular type of periodicbreathing involving a gradual waxing and waning of tidal volume andhaving a central apnea and hyperpnea event in each cycle. Othermanifestations of periodic breathing are also possible. The variousforms of disordered breathing may be determined based on thecharacteristic respiration patterns associated with particular types ofdisordered breathing.

As illustrated in FIGS. 15A-E, a respiration pattern detected as adisordered breathing episode may include only an apnea respiration cycle1510 (FIG. 15A), only hypopnea respiration cycles 1550 (FIG. 15D), or amixture of hypopnea and apnea respiration cycles 1520 (FIG. 15B), 1530(FIG. 15C), 1560 (FIG. 15E). A disordered breathing event 1520 may beginwith an apnea respiration cycle and end with one or more hypopneacycles. In another pattern, the disordered breathing event 1530 maybegin with hypopnea cycles and end with an apnea cycle. In yet anotherpattern, a disordered breathing event 1560 may begin and end withhypopnea cycles with an apnea cycle in between the hypopnea cycles.

FIG. 16 is a flow graph of a method for detecting disordered breathingin accordance with embodiments of the invention. The method illustratedin FIG. 16 operates by classifying breathing patterns using breathintervals in conjunction with tidal volume and duration thresholds aspreviously described above. In this example, a duration threshold and atidal volume threshold are established for determining both apnea andhypopnea breath intervals. An apnea episode is detected if the breathinterval exceeds the duration threshold. A hypopnea episode is detectedif the tidal volume of successive breaths remains less than the tidalvolume threshold for a period in excess of the duration threshold. Mixedapnea/hypopnea episodes may also occur. In these cases, the period ofdisordered breathing is characterized by shallow breaths ornon-breathing intervals. During the mixed apnea/hypopnea episodes, thetidal volume of each breath remains less than the tidal volume thresholdfor a period exceeding the duration threshold.

Transthoracic impedance is sensed and used to determine the patient'srespiration cycles. Each breath 1610 may be characterized by a breathinterval, the interval of time between two impedance signal maxima, anda tidal volume (TV).

If a breath interval exceeds 1615 the duration threshold, then therespiration pattern is consistent with an apnea event, and an apneaevent trigger is turned on 1620. If the tidal volume of the breathinterval exceeds 1625 the tidal volume threshold, then the breathingpattern is characterized by two respiration cycles of normal volumeseparated by a non-breathing interval. This pattern represents a purelyapneic disordered breathing event, and apnea is detected 1630. Becausethe final breath of the breath interval was normal, the apnea eventtrigger is turned off 1632, signaling the end of the disorderedbreathing episode. However, if the tidal volume of the breath intervaldoes not exceed 1625 the tidal volume threshold, the disorderedbreathing period is continuing and the next breath is checked 1610.

If the breath interval does not exceed 1615 the duration threshold, thenthe tidal volume of the breath is checked 1635. If the tidal volume doesnot exceed 1635 the tidal volume threshold, the breathing pattern isconsistent with a hypopnea cycle and a hypopnea event trigger is set on1640. If the tidal volume exceeds the tidal volume threshold, then thebreath is normal.

If a period of disordered breathing is in progress, detection of anormal breath signals the end of the disordered breathing. If disorderedbreathing was previously detected 1645, and if the disordered breathingevent duration has not exceeded 1650 the duration threshold, and thecurrent breath is normal, then no disordered breathing event is detected1655. If disordered breathing was previously detected 1645, and if thedisordered breathing event duration has extended for a period of timeexceeding 1650 the duration threshold, and the current breath is normal,then the disordered breathing trigger is turned off 1660. In thissituation, the duration of the disordered breathing episode was ofsufficient duration to be classified as a disordered breathing episode.If an apnea event was previously triggered 1665, then an apnea event isdeclared 1670. If a hypopnea was previously triggered 1665, then ahypopnea event is declared 1675.

In accordance with various embodiments of the invention a disorderedbreathing event may be classified as a central disordered breathingevent, an obstructive disordered breathing event, or a mixed disorderedbreathing event comprising both central and obstructive types.Classification of the disordered breathing event by these processesinvolves evaluating chest wall motion or other motion associated withrespiratory effort. FIGS. 17A and 17B provide graphs of accelerometersignals representing chest wall motion for central and obstructivedisordered breathing, respectively. As illustrated in FIG. 17A, apnea isdetected when the transthoracic impedance signal 1710 remains below aninspiration threshold 1715 for a period of time greater than an apneainterval 1717, e.g., 10 seconds. In this example, the apnea event is acentral apnea event and the signal 1720 from an accelerometer sensingthe patient's chest wall motion also falls below a motion threshold 1725during the period of non-respiration. The lack of chest wall motionindicates that the patient's breathing reflex is not being triggered bythe central nervous system, indicative of a central disordered breathingevent.

FIG. 17B illustrates the accelerometer signal and transthoracicimpedance signal for an obstructive apnea event. Apnea is detected whenthe transthoracic impedance signal 1750 remains below an inspirationthreshold 1755 for a period of time greater than an apnea interval 1757.In this example, the apnea event is an obstructive apnea event and thesignal 1760 from an accelerometer sensing the patient's chest wallmotion rises above a chest well motion threshold 1765 during the periodof non-respiration. The chest wall motion indicates that the patient'sbreathing reflex is being triggered by the central nervous system,indicative of an obstructive disordered breathing event.

FIG. 18A is a flowchart of a method for classifying disordered breathingevents as central, obstructive or mixed events in accordance withembodiments of the invention. One or more conditions associated withdisordered breathing are sensed 1805. For example, one or more of theconditions listed in Table 1 may be sensed to detect that a disorderedbreathing event is occurring. The patient's chest wall motion is sensed1810 during the disordered breathing event.

If disordered breathing is detected 1815, then the chest wall motionsignals are analyzed 1820 for obstructive/central origin discrimination.A parameter, e.g., average amplitude or frequency, of the signalproduced by the motion sensor may be compared to a threshold. If thechest wall motion signal is not greater 1825 than a threshold, then thedisordered breathing is classified 1830 as central disordered breathing.If the chest wall motion signal is greater than or equal to thethreshold 1825 and the chest wall motion is associated with respiratoryeffort 1835, then the disordered breathing is classified 1837 asobstructive disordered breathing. For example, if chest wall motion fromthe accelerometer is synchronous with a reduced transthoracic impedanceduring a disordered breathing episode, then the concurrence ofdisordered breathing and chest wall motion indicates disorderedbreathing that is obstructive in origin.

If the disordered breathing event continues 1840, then chest wall motioncontinues to be sensed 1820. A second or subsequent portion of thedisordered breathing event may have a different classification from theinitial classification based on the presence or lack of motionassociated with respiratory effort.

The flowchart of FIG. 18B follows from FIG. 18A and illustrates optionalprocesses that may be implemented following classification of thedisordered breathing event. Disordered breathing information mayoptionally be stored, transmitted, displayed, and/or printed 1845. Forexample, disordered breathing information may be stored over severalweeks or months to enhance diagnosis of disordered breathing or otherconditions, or to analyze disordered breathing trends and/or therapyeffectiveness.

Additionally, or alternatively, classification of the origin ofdisordered breathing events may be used in connection with providing1850 a therapy to treat the disordered breathing. Therapy for treatingdisordered breathing may involve cardiac pacing therapy, nervestimulation therapy, respiration therapy such as that provided by anxPAP device, among other therapies. In one scenario, a first therapy maybe used to treat disordered breathing that is central in origin. Asecond therapy may be used to treat disordered breathing that isobstructive in origin. The first and/or the second therapies may beinitiated after the origin of the disordered breathing is determined.

Further, therapies other than disordered breathing therapy may beinitiated, modified, or terminated 1855 based on the classification ofdisordered breathing. For example, as previously discussed, disorderedbreathing in the form of Cheyne-Stokes respiration is related tocongestive heart failure and may be used to monitor the progression ofCHF. As previously discussed, Cheyne-Stokes respiration is marked byperiodic patterns of waxing and waning respiration interrupted byperiods of central apnea. Characteristics of the disordered breathingexperienced by the patient, e.g., origin, duration, and severity, may beused to initiate or adjust therapy, such as cardiac pacing therapyand/or cardiac resynchronization therapy, delivered to the patient.

In various embodiments of the invention described herein, discriminationbetween central and obstructive disordered breathing is based on sensingchest wall motion using an implanted motion sensor, e.g., anaccelerometer. In other embodiments, a patient-external motion detector,such as a patient-external accelerometer, patient-external respiratorybands, transthoracic impedance sensor, or a mercury switch, may be usedalone or in combination with other implanted or patient-externalrespiratory sensors and detection algorithms for central/obstructivedisordered breathing classification.

In one example, a movement sensor, such as an accelerometer, is mountedinside an implantable CRM device to sense chest wall motions that areindicative of obstructive apnea to determine if the sensed chest wallmotions are indicative of obstructive apnea. The output of the movementsensor may be used in combination with other sensors (such astrans-thoracic impedance) for classification of obstructive apnea.

Multi-sensor pulse generators are products in a unique position toprovide accurate long-term monitoring and prediction of the progressionof disease in patients with disordered breathing. Discrimination betweentypes of apnea events provides more accurate diagnosis and monitoring ofabnormal respiration patterns associated with CHF or sleep disorderedbreathing. Monitoring with discrimination between types of apnea mayenable therapy improvements to counteract the effects of abnormalrespiratory patterns. Cardiac pacing has been used as an effectivetherapy for disordered breathing. Methods and systems for providing anadaptive cardiac electrical stimulation therapy for disordered breathingare described in commonly owned U.S. patent application entitled“Adaptive Therapy for Disordered Breathing,” Ser. No. 10/643,203,attorney docket number GUID.059PA, filed Aug. 18, 2003 which isincorporated by reference.

Although episodes of disordered breathing can occur when the patient isawake, they most frequently occur during sleep. Sleep detection may beused in concert with discrimination of central and obstructivedisordered breathing events for enhanced detection of central andobstructive sleep apnea and/or other forms of disordered breathing.Methods and systems for detecting sleep are described in commonly ownedU.S. patent application entitled “Sleep Detection Using an AdjustableThreshold,” Ser. No. 10/309,771, attorney docket number GUID.064PA,filed Dec. 4, 2002 which is incorporated by reference.

Methods and systems for detecting REM sleep and/or other sleep statesare described in commonly owned U.S. patent application entitled “SleepState Classification,” Ser. No. 10/643,006, attorney docket numberGUID.060PA, filed Aug. 18, 2003 which is incorporated by reference.

The methods and systems described above provide enhanced disorderedbreathing discrimination, providing more accurate diagnostic informationfor disordered breathing. Discrimination between central and obstructivedisordered breathing may be particularly useful in connection withmonitoring the abnormal breathing patterns of congestive heart failurepatients. The improved monitoring may enable therapy improvements tocounteract the effect of disordered breathing and/or CHF.

A number of the examples presented herein involve block diagramsillustrating functional blocks used for monitoring functions inaccordance with embodiments of the present invention. It will beunderstood by those skilled in the art that there exist many possibleconfigurations in which these functional blocks can be arranged andimplemented. The examples depicted herein provide examples of possiblefunctional arrangements used to implement the approaches of theinvention. The components and functionality depicted as separate ordiscrete blocks/elements in the figures in general can be implemented incombination with other components and functionality. The depiction ofsuch components and functionality in individual or integral form is forpurposes of clarity of explanation, and not of limitation. It is alsounderstood that the components and functionality depicted in the Figuresand described herein can be implemented in hardware, software, or acombination of hardware and software.

1. A method for classifying disordered breathing in a patient,comprising: detecting a disordered breathing event; sensing motionassociated with respiratory effort during the disordered breathingevent; and classifying the disordered breathing event based on thesensed motion, wherein at least one of detecting, sensing, andclassifying is performed at least in part implantably.
 2. The method ofclaim 1, wherein at least two of detecting, sensing, and classifying areperformed at least in part implantably.
 3. The method of claim 1,wherein all of detecting, sensing, and classifying are performed atleast in part implantably.
 4. The method of claim 1, wherein thedisordered breathing event comprises Cheyne-Stokes respiration.
 5. Themethod of claim 1, wherein the disordered breathing event comprisesperiodic breathing.
 6. The method of claim 1, wherein the disorderedbreathing event comprises apnea.
 7. The method of claim 1, wherein thedisordered breathing event comprises hypopnea.
 8. The method of claim 1,wherein the disordered breathing event comprises sleep disorderedbreathing.
 9. The method of claim 1, wherein detecting the disorderedbreathing event comprises detecting the disordered breathing event basedon respiration patterns.
 10. The method of claim 1, wherein detectingthe disordered breathing event comprises detecting the disorderedbreathing event based on blood gas level.
 11. The method of claim 1,wherein detecting the disordered breathing event comprises detecting thedisordered breathing event based on transthoracic impedancemeasurements.
 12. The method of claim 1, wherein detecting thedisordered breathing event comprises detecting the disordered breathingevent based on respiratory system conditions.
 13. The method of claim 1,wherein detecting the disordered breathing event comprises detecting thedisordered breathing event based on cardiovascular system conditions.14. The method of claim 1, wherein detecting the disordered breathingevent comprises detecting the disordered breathing event based oncardiopulmonary conditions.
 15. The method of claim 1, wherein detectingthe disordered breathing event comprises detecting the disorderedbreathing event based on nervous system conditions.
 16. The method ofclaim 1, wherein detecting the disordered breathing event comprisesdetecting the disordered breathing event based on non-physiologicalconditions.
 17. The method of claim 1, wherein sensing the motionassociated with respiratory effort during the disordered breathing eventcomprises sensing chest wall motion associated with the respiratoryeffort.
 18. The method of claim 1, wherein sensing the motion associatedwith respiratory effort during the disordered breathing event comprisessensing abdominal motion associated with respiratory effort.
 19. Themethod of claim 1, wherein sensing the motion associated withrespiratory effort during the disordered breathing event comprisesdistinguishing the motion associated with respiratory effort from othertypes of motion.
 20. The method of claim 1, wherein classifying thedisordered breathing event comprises classifying the disorderedbreathing event as a central disordered breathing event.
 21. The methodof claim 1, wherein classifying the disordered breathing event comprisesclassifying the disordered breathing event as an obstructive disorderedbreathing event.
 22. The method of claim 1, wherein classifying thedisordered breathing event as a mixed central and obstructive disorderedbreathing event.
 23. The method of claim 1, wherein classifying thedisordered breathing event comprises classifying the disorderedbreathing event as an obstructive disordered if the motion associatedwith respiratory effort during the disordered breathing event is equalto or above a motion threshold.
 24. The method of claim 1, whereinclassifying the disordered breathing event comprises classifying thedisordered breathing event as a central disordered breathing event ifmotion associated with respiratory effort is below a motion threshold.25. The method of claim 1, wherein classifying the disordered breathingevent comprises classifying the disordered breathing event as a mixedcentral and obstructive disordered breathing event if the motionassociated with respiratory effort is equal to or above a motionthreshold during a first portion of the disordered breathing event andthe motion associated with respiratory effort is below the motionthreshold during a second portion of the disordered breathing event. 26.The method of claim 1, wherein classifying the disordered breathingevent comprises discriminating between central disordered breathing andobstructive disordered breathing.
 27. The method of claim 1, furthercomprising storing information associated with the disordered breathingevent.
 28. The method of claim 1, further comprising transmittinginformation associated with the disordered breathing event.
 29. Themethod of claim 1, further comprising displaying information associatedwith the disordered breathing event.
 30. The method of claim 1, furthercomprising using the classification of the disordered breathing event toevaluate disordered breathing trends.
 31. The method of claim 1, furthercomprising delivering a therapy to treat disordered breathing based onthe classification of the disordered breathing event.
 32. The method ofclaim 1, further comprising modifying a therapy delivered to the patientbased on the classification of the disordered breathing event.
 33. Themethod of claim 32, wherein the modified therapy is a disorderedbreathing therapy.
 34. A system for classifying disordered breathing,comprising: a disordered breathing detector configured to detect adisordered breathing event; a motion sensor configured to sense motionassociated with respiratory effort of a patient during the disorderedbreathing event; and a disordered breathing classification processorcoupled to the motion sensor and the disordered breathing detector, thedisordered breathing classification processor configured to classify thedisordered breathing event based on the respiratory effort motion,wherein at least one of the disordered breathing detector, the motionsensor, and the disordered breathing classification processor is atleast in part implantable.
 35. The system of claim 34, wherein at leasttwo of the disordered breathing detector, the motion sensor, and thedisordered breathing classification processor are at least in partimplantable.
 36. The system of claim 34, wherein the disorderedbreathing detector, the motion sensor, and the disordered breathingclassification processor are at least in part implantable.
 37. Thesystem of claim 34, wherein the disordered breathing detector comprisesa sensor configured to sense patient respiration.
 38. The system ofclaim 37, wherein the respiration sensor comprises a transthoracicimpedance sensor.
 39. The system of claim 37, wherein the respirationsensor comprises a microphone configured to detect snoring sounds. 40.The system of claim 37, wherein the respiration sensor comprises anairflow sensor.
 41. The system of claim 37, wherein the respirationsensor comprises a sensor configured to sense blood gas.
 42. The systemof claim 34, wherein the disordered breathing detector comprises asensor configured to sense cardiovascular system conditions.
 43. Thesystem of claim 34, wherein the disordered breathing detector comprisesa sensor configured to sense respiration system conditions.
 44. Thesystem of claim 34, wherein the disordered breathing detector comprisesa sensor configured to sense nervous system conditions.
 45. The systemof claim 34, wherein the disordered breathing detector comprises asensor configured to sense muscle system conditions.
 46. The system ofclaim 34, wherein the disordered breathing detector comprises a sensorconfigured to sense non-physiological conditions.
 47. The system ofclaim 34, wherein the motion sensor comprises an accelerometer.
 48. Thesystem of claim 34, wherein the motion sensor comprises a transthoracicimpedance sensor.
 49. The system of claim 34, wherein the motion sensorcomprises a respiratory band.
 50. The system of claim 34, wherein themotion sensor comprises a switch.
 51. The system of claim 34, whereinthe motion sensor comprises an electromyogram sensor.
 52. The system ofclaim 34, wherein the motion sensor is configured to sense chest wallmotion.
 53. The system of claim 34, wherein the motion sensor isconfigured to sense abdominal motion.
 54. The system of claim 34,wherein the disordered breathing classification processor is configuredto classify the disordered breathing event as a central disorderedbreathing event.
 55. The system of claim 34, wherein the disorderedbreathing classification processor is configured to classify thedisordered breathing event as an obstructive disordered breathing event.56. The system of claim 34, wherein the disordered breathingclassification processor is configured to classify the disorderedbreathing event as a mixed central and obstructive disordered breathingevent.
 57. The system of claim 34, wherein the disordered breathingclassification processor is configured to discriminate between centraland obstructive disordered breathing.
 58. The system of claim 34,wherein the disordered breathing classification processor is configuredto classify the disordered breathing event as an obstructive disorderedbreathing event if the motion associated with respiratory effort duringthe disordered breathing event is equal to or above a motion threshold.59. The system of claim 34, wherein the disordered breathingclassification processor is configured to classify the disorderedbreathing event as a central disordered breathing event if the motionassociated with respiratory effort during the disordered breathing eventis below a motion threshold.
 60. The system of claim 34, wherein thedisordered breathing classification processor is configured to classifythe disordered breathing event as an obstructive disordered breathingevent if the motion associated with respiratory effort during thedisordered breathing event is equal to or above a motion thresholdduring a first portion of the disordered breathing event and classifythe disordered breathing event as a central disordered breathing eventif the motion associated with respiratory effort during the disorderedbreathing event is below a motion threshold during a second portion ofthe disordered breathing event.
 61. The system of claim 34, wherein thedisordered breathing classification processor is configured todistinguish between the motion associated with respiratory effort andother types of motion.
 62. The system of claim 34, wherein at least oneof the motion sensor and the disordered breathing detector is wirelesslycoupled to the disordered breathing classification processor.
 63. Thesystem of claim 34, wherein at least one of the motion sensor, thedisordered breathing detector, and the disordered breathingclassification processor is mechanically coupled to a cardiac rhythmmanagement device.
 64. The system of claim 34, wherein at least one ofthe motion sensor, the disordered breathing detector, and the disorderedbreathing classification processor is a mechanically coupled to apositive airway pressure device.
 65. The system of claim 34, wherein atleast one of the motion sensor, the disordered breathing detector, andthe disordered breathing classification processor are coupled to apatient management system.
 66. The system of claim 34, furthercomprising a memory coupled to the disordered breathing classificationprocessor and configured to store information about the disorderedbreathing event.
 67. The system of claim 34, further comprising adisplay device coupled to the disordered breathing classificationprocessor and configured to display information about the disorderedbreathing event.
 68. The system of claim 34, further comprising atherapy unit coupled to the disordered breathing classificationprocessor and configured to deliver therapy to the patient to treatdisordered breathing.
 69. The system of claim 34, further comprising atherapy delivery unit coupled to the disordered breathing classificationprocessor and configured to modify a therapy delivered to the patientbased on the classification of the disordered breathing event.
 70. Adisordered breathing classification system, comprising: means fordetecting a disordered breathing event; means for sensing motionassociated with respiratory effort during the disordered breathingevent; and means for classifying the disordered breathing event based onthe sensed motion, wherein at least one of the means for sensing, themeans for detecting, and the means for classifying is at lease partiallyimplantable.
 71. The system of claim 70, further comprising means forstoring information associated with the disordered breathing event. 72.The system of claim 70, further comprising means for transmittinginformation associated with the disordered breathing event.
 73. Thesystem of claim 70, further comprising means for displaying informationassociated with the disordered breathing event.
 74. The system of claim70, further comprising means for using the classification of thedisordered breathing event to evaluate disordered breathing trends. 75.The system of claim 70, further comprising means for delivering atherapy for disordered breathing based on the classification of thedisordered breathing event.
 76. The system of claim 70, furthercomprising means for modifying a therapy delivered to the patient basedon the classification of the disordered breathing event.